برآورد سرعت وسایل نقلیه متحرک در مسیرهای دایروی با استفاده از دو حسگر بردار صوتی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد دانشکده مهندسی مکانیک و انرژی دانشگاه شهید بهشتی

2 دانشگاه شهید بهشتی، پردیس فنی و مهندسی شهید عباسپور، استادیار دانشکده مهندسی مکانیک و انرژی

3 دانشیار دانشکده مهندسی مکانیک و انرژی دانشگاه شهید بهشتی

4 گروه مهندسی مکانیک دانشگاه تفرش

چکیده

امروزه روش‌ها و تجهیزات متعددی برای برآورد و یا تخمین سرعت وسیله نقلیه متحرک وجود دارد که بسیاری از آنها به‌دلیل شرایط نصب و ملزومات مورد نیاز گران قیمت هستند. یکی از این روش‌ها استفاده از کمیت شدت صوتی است. حسگرهای بردار صوتی که جزء حسگرهای غیرفعال هستند، می‌توانند مقادیر شدت صوتی را از محیط به‌دست آوردند. در این مقاله با استفاده از دو حسگر بردار صوتی، میانگین سرعت وسایل نقلیه متحرک در مسیرهای دایروی شکل به‌دست می‌آید. در این روش برای به‌دست آوردن سرعت ابتدا لازم است مکان منبع تخمین زده شود. یک حسگر بردار صوتی به تنهایی قادر نیست مکان منبع صوت را تعیین کند و تنها می‌تواند برآورد جهت رسیدن (DoA) را انجام دهد. با استفاده از دو حسگر و تعیین محل تقاطع پرتوهای هر حسگر می‌توان محل منبع صوت را تشخیص داد. روش‌ها و معادلات حاکم بر این روش در این مقاله ارائه می‌شود. در انتها نیز به بررسی نتایج عددی پرداخته می‌شود. در این مقاله مسیرهای دایروی مختلفی مورد تحلیل قرار گرفته است. نتایج نشان می‌دهد روش پیشنهادی به‌خوبی به تخمین مکان و سرعت وسیله نقلیه متحرک در زمان‌های مختلف می‌پردازد. 


 


 

 
 

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Estimation of the speed of moving vehicles in a circular path using two sound vector sensors

نویسندگان [English]

  • Amirhosein Arab 1
  • Abbas Rahi 2
  • Morteza Shahravi 3
  • Abolfazl Hasani Baferani 4
1 Shahoid Beheshti Univ.
2 Faculty of Mechanical and Energy Engineering, Shahid Beheshti University, Tehran, Iran
3 Shahid Beheshti Univ.
4 Department of Mechanical Engineering Tafresh University
چکیده [English]

Today, there are many methods and equipment for estimating the speed of a moving vehicle, which many of them are expensive due to the installation conditions and requirements. One of these methods is the use of sound intensity quantity. Sound vector sensors, which are passive sensors, can obtain sound intensity values from the environment. In this article, using two sound vector sensors, the average speed of moving vehicles in circular paths is obtained. In this method, to get the speed, it is necessary to estimate the location of the source first. A sound vector sensor alone cannot determine the location of the sound source and can only estimate the direction of arrival (DoA). By using two sensors and determining the intersection of the rays of each sensor, the location of the sound source can be detected. The methods and equations governing this method are presented in this article. In the end, the numerical results are analyzed. In this article, various circular paths have been studied. The results show that the proposed method is good at estimating the location and speed of the moving vehicle at different times.

کلیدواژه‌ها [English]

  • Estimation of average speed
  • sound vector sensor
  • localization
  • estimation of sound source position
[1] Klein, Lawrence A., Milton K. Mills, and David RP Gibson, Traffic detector handbook: Volume I. No. FHWA-HRT-06-108, Turner-Fairbank Highway Research Center, 2006.
[2] Adnan, Muhammad Akram, Norliana Sulaiman, Nor Izzah Zainuddin, and Tuan Badrul Hisyam Tuan Besar, "Vehicle speed measurement technique using various speed detection instrumentation", In 2013 IEEE Business Engineering and Industrial Applications Colloquium (BEIAC), 2013, IEEE, pp.668-672.
[3] Guerrero-Ibáñez, Juan, Sherali Zeadally, and Juan Contreras-Castillo, "Sensor technologies for intelligent transportation systems", Sensors, 2018, Vol.18, no.4, p.1212.
[4] Manaa, Karmel, Maram Rabee’a, and Loay Khalaf, "Traffic control by digital imaging cameras", In Emerging Trends in Image Processing, Computer Vision and Pattern Recognition, Morgan Kaufmann, 2015, pp. 231-247.
[5] Yang, Zi, and Lilian SC Pun-Cheng, "Vehicle detection in intelligent transportation systems and its applications under varying environments: A review", Image and Vision Computing, 2018, Vol.69, pp.143-154.
[6] Darwish, Tasneem, and K. Abu Bakar, "Traffic density estimation in vehicular ad hoc networks: A review", Ad Hoc Networks, 2015, Vol.24, pp.337-351.
[7] Lahrmann, Harry Spaabæk, Bo Brassøe, Jonas Wibert Johansen, and Jens Christian Overgaard Madsen, "Safety impact of average speed control in the UK", Journal of transportation technologies, 2016, Vol.6, no.5, pp.312-326.
[8] Du, Rong, Paolo Santi, Ming Xiao, Athanasios V. Vasilakos, and Carlo Fischione, "The sensable city: A survey on the deployment and management for smart city monitoring", IEEE Communications Surveys & Tutorials, 2018, Vol.21, no.2, pp.1533-1560.
[9] Cao, Jiuwen, Jun Liu, Jianzhong Wang, and Xiaoping Lai, "Acoustic vector sensor: reviews and future perspectives", IET Signal Processing, 2017, Vol.11, no.1, pp.1-9.
[10] Jacobsen, Finn, and Hans-Elias De Bree, "The microflown particle velocity sensor", In Handbook of Signal Processing in Acoustics, New York, NY: Springer New York, 2008, pp. 1283-1291.
[11] Yang, Xiaowei, Gang Zhu, and Yinxiao Miao, "Calibration of sound intensity instruments based on the double coupler technology", Applied Acoustics, 2022, Vol.199, p.109008.
[12] Kotus, Józef. "Multiple sound sources localization in free field using acoustic vector sensor." Multimedia tools and applications 74 (2015): 4235-4251.
[13] Kotus, Jozef. "Determination of the vehicles speed using acoustic vector sensor", In 2018 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), 2018, IEEE, 2018, pp.64-69.
[14] Czyżewski, Andrzej, Józef Kotus, and Grzegorz Szwoch, "Estimating traffic intensity employing passive acoustic radar and enhanced microwave doppler radar sensor", Remote Sensing, 2019, Vol.12, no.1, p.110.
[15] Kotus, Józef, and Grzegorz Szwoch, "Estimation of average speed of road vehicles by sound intensity analysis", Sensors, 2021, Vol.21, no.16, p.5337.
[16] Szwoch, Grzegorz, and Józef Kotus, "Acoustic detector of road vehicles based on sound intensity", Sensors, 2021, Vol.21, no.23, p.7781.
[17] Salomons, Erik, Dirk Van Maercke, Jérôme Defrance, and Foort De Roo, "The Harmonoise sound propagation model", Acta acustica united with Acustica, 2011, Vol.97, no.1, pp.62-74.
[18] Na, Yueyue, Yanmeng Guo, Qiang Fu, and Yonghong Yan, "An acoustic traffic monitoring system: Design and implementation", In 2015 IEEE 12th Intl Conf on Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom), IEEE, 2015, pp.119-126.
[19] Barbagli, Barbara, Gianfranco Manes, Rodolfo Facchini, and Antonio Manes, "Acoustic sensor network for vehicle traffic monitoring", In Proceedings of the 1st international conference on advances in vehicular systems, technologies and applications, 2012, pp.24-29.
[20] Chen, Shiping, Ziping Sun, and Bryan Bridge, "Traffic monitoring using digital sound field mapping", IEEE Transactions on vehicular technology, 2001, Vol.50, no.6, pp.1582-1589.
[21] Duffner, Orla, Sean Marlow, Noel Murphy, Noel O'Connor, and Alan Smeanton, "Road traffic monitoring using a two-microphone array", In Audio Engineering Society Convention 118, Audio Engineering Society, 2005.
[22] López-Valcarce, Roberto, Carlos Mosquera, and Fernando Pérez-González, "Estimation of road vehicle speed using two omnidirectional microphones: A maximum likelihood approach", EURASIP Journal on Advances in Signal Processing, 2004, pp.1-19.
[23] Cevher, Volkan, Rama Chellappa, and James H. McClellan, "Vehicle speed estimation using acoustic wave patterns", IEEE Transactions on signal processing, 2008, Vol.57, no.1, pp.30-47.
[24] Ishida, Shigemi, Song Liu, Kohei Mimura, Shigeaki Tagashira, and Akira Fukuda, "Design of acoustic vehicle count system using DTW", In Proc. ITS World Congress, 2016, pp.1-10.
[25] Warghade, Vasant P., and Mangesh S. Deshpande, "Road traffic condition estimation based on road acoustics", In 2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA), IEEE, 2017, pp. 1-5.
[26] Gatto, Rubens Cruz, and Carlos Henrique Quartucci Forster, "Audio-based machine learning model for traffic congestion detection", IEEE Transactions on Intelligent Transportation Systems, 2020, Vol.22, no.11, pp.7200-7207.
[27] Vij, Dinesh, and Naveen Aggarwal, "Smartphone based traffic state detection using acoustic analysis and crowdsourcing", Applied Acoustics, 2018, Vol.138, pp.80-91.
[28] Arab, Amirhosein, Abbas Rahi, Morteza Shahravi, and Abolfazl Hasani Baferani, "Investigating the error of object position estimation using two sound vector sensors", Journal of Vibration and Sound, 2023.